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      Integral perception, but separate processing: The perceptual normalization of lexical tones and vowels

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      Neuropsychologia
      Elsevier BV

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          Fitting Linear Mixed-Effects Models Usinglme4

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            EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

            We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
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              The assessment and analysis of handedness: The Edinburgh inventory

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                Author and article information

                Contributors
                Journal
                Neuropsychologia
                Neuropsychologia
                Elsevier BV
                00283932
                June 2021
                June 2021
                : 156
                : 107839
                Article
                10.1016/j.neuropsychologia.2021.107839
                33798490
                f3f133f8-74d5-44bf-aee6-9e7ef3aafc5a
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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